{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 可视化图分哪些？\n",
    "\n",
    "按照数据之间的关系，我们可以吧可视化视图分为4类，他们分别是比较，联系，构成和分布。\n",
    "1. 比较： 比较数据间的各类别的关系，或者时他们随着时间的变化趋势，比如折线图\n",
    "2. 联系： 查看两个或者两个变量以上的关系，比如散点图\n",
    "3. 构成： 每个部分占整体的百分比，或者是随着时间的百分比变化，比如饼图\n",
    "4. 分布： 关注单个变量，或者多个变量的分布情况，比如直方图\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 散点图\n",
    "\n",
    "散点图的英文叫做 scatter plot ，它将两个变量的值显示在二维坐标中，非常适合展示两个变量之间的关系。当然，除了二维的散点图，我们还有三维的散点\n",
    "图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "N = 1000\n",
    "x = np.random.randn(N)\n",
    "y = np.random.randn(N)\n",
    "\n",
    "# 使用Matplotlib画散点图\n",
    "plt.scatter(x, y, marker='x')\n",
    "plt.show()\n",
    "\n",
    "# 使用seaborn画散点图\n",
    "df = pd.DataFrame({'x': x, 'y': y})\n",
    "sns.jointplot(x=\"x\", y = \"y\", data=df, kind='scatter')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 折线图\n",
    "\n",
    "用来表示数据随着时间变化的趋势"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import random\n",
    "\n",
    "# 数据准备\n",
    "x = [i for i in range(2010, 2020)]\n",
    "y = [5,3,6,20,17,16,19,30,32,35]\n",
    "\n",
    "# 使用Seaborn画折线图\n",
    "plt.plot(x,y)\n",
    "plt.show()\n",
    "\n",
    "# 使用Seaborn画折线图\n",
    "\n",
    "df = pd.DataFrame({'x': x, 'y': y})\n",
    "sns.lineplot(x='x', y='y', data= df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 直方图\n",
    "\n",
    "它是把横坐标等分成了一定数量的小区间，这个小区间也叫作 “ 箱子 ” ，然后在每个 “ 箱子 ” 内用矩形条（ bars ）展示该箱子的箱子数\n",
    "（也就是 y 值），这样就完成了对数据集的直方图分布的可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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FW/H9SpK4tXpPAz4zFk3M9TrKeZtVlM3ItCT+sDN+9qGXxKRClyF3oiPE2/uPMKc4m6zUJK/jnDe/z7h8aj6v7aonFNZCo+IdFboMubf3N9IRCifU0ZVXTi+g8XgHm6u1nK54R4UuQyoUdqyuaKB0VBpFI+PvQKKzuXxqPj6DV3fUeR1FhjEVugyp7YeaONramVCjc4CctGQuHDeSV3aq0MU7KnQZUqv3HGZkWhIzx2Z5HSXqrpxewJYDTdQ1tXkdRYap+Fh4WhLCgSMn2NfQynWzCmP6QKKBrBgJnFoX/Zu/28F3bpsXzUgiEdEIXYbM6j2HSQ74KCuN/10Ve1OYlUpWaoAdNc1eR5FhSoUuQ6KprZPN1cdYMG4kqUl+r+MMCjNjxpgsdtc109oR9DqODEMqdBkSaysaCTvHxZNGeR1lUM0uyqYz5Hh5uz4claGnQpdB1xkKs3ZvA9MKM8nLSPE6zqAqzUsnMyXA85vPddpdkcGhQpdBt6nqKK0dIZbE6Zrn/eEz6zqV3s56nfRChpwKXQaVc47VexoozEplYl6613GGxJzibDqCYV7aXut1FBlmVOgyqPbUH6emqY0lk0dhMbyrYjSV5KYxJjuV5zcd8jqKDDMqdBlUq8oPk57sZ05xfK953h8+M66fPYY/7q7nWKumXWToqNBl0NQ2tbGztpnFk+J/zfP++vD8IjpDjl9vPOB1FBlGhterTIbUqvLDBHzG4gmJvatib2YVZTO3OJvH1+zHOS2pK0NDhS6Doqmtk3eqjrJg/EjSU4bnChMfXzye8roW1u5t9DqKDBMqdBkUa/Y0EA67YbGr4tncMGcsWakBnliz3+soMkxEVOhmttTMdppZuZnd38vtf2Nm28xss5m9bGbjox9V4kV7MMTavY3MHJuV8AcSncuIZD+3lJXw+y011DVrBUYZfH0Wupn5gUeAa4GZwB1mNvOMzd4Bypxzc4BfAN+KdlCJH2/vP8KJzhCXDePR+UkfXzSOYNix7K0qr6PIMBDJCH0hUO6cq3DOdQDLgJt6buCce9U519p9cQ1QHN2YEi9CYceq8sOMy01j3KjhcSDRuUzMz+Cq6QX8+I29NOnIURlkkRR6EdBzeFHdfd3Z/AXwu/MJJfFr68FjHGnt5LIpGp2f9NdXT+XYiU4ee2Ov11EkwUVS6L0d3tfrflhmdidQBjx8ltvvNbP1Zra+vr4+8pQSF5xzvFF+mFHpycwYk3hnJBqo2cXZLL2gkB+/vpejrR1ex5EEFkmhVwMlPS4XA+9ZSs7Mrga+AtzonGvv7Y6cc48658qcc2X5+fkDySsxbO3eRqqPnGDJ5LyYPiORF/76mqm0dAR59I8VXkeRBBZJoa8DppjZBDNLBm4HlvfcwMzmAz+gq8y1EPQw9f9f2U16SoALx430OkrMmVaYyQ1zxvJfq/ZR1dja9zeIDECfhe6cCwL3ASuB7cAzzrmtZvaQmd3YvdnDQAbwczPbaGbLz3J3kqDe2tvIqvIGLp+SR3JAhzf05svXTsdn8MAv39XRozIoIjqEzzm3AlhxxnUP9vj66ijnkjjz3Rd3kZeRwsJheJh/pIpyRvDAdTP46q+38Mz6Km67aJzXkSTBDM9jsiWq1lQ08GZFA1+9foZG53342MJxPL/5IF9/fjvvm5rPmOwRvW731NrK83+sRfoPY7jRq0/Oi3OO77y4i/zMFO5crAOE++LzGf/y0TmEnOMzT2ygrTPkdSRJICp0OS8vbqvlrb2NfP6qyaQm+b2OExfGj0rnO7fOY1PVUc2nS1Sp0GXAOoJhvvG7HUwuyOCOhXp73x9LZxXypWum8qt3DvDvr+3xOo4kCM2hy4A9uXY/ew8f57FPlhEYZiewiIb7rprM7roWHl65k8zUAJ+4uNTrSBLnVOgyIEdbO/jey7u5dHIeV04r8DpOXDIzvn3rXE50hnjwN1sJ+Hz6IFPOi4ZVMiD/vGI7zW1BvnL9jGFz8ufBkOT38f2PzefKafn83a/e5XGtnS7nQSN06bfV5Yd5Zn01n71iktZsiYKUgJ//uHMBf/XkBv7+11to7wyRlqyXpvSfRujSL22dIR741buUjkrjC++f4nWchJGa5Oc/71zAdbML+fpvt/PqTq2gIf2nYYD0y7df2Mn+hlae+vQi7aYYZckBH/92+3xSApv51TsH6AyGuWbmaE1pScRU6BKx13bW8cPX93Ln4nFcMknrnQ+GgN/Ht2+ZS/WRVl7bVU9nKMx1s8eo1CUiKnSJSG1TG196ZhPTCzP56vVnnoFQosnnMz48r4iA38eqPQ0kB/xcM3O017EkDqjQpU/BUJgvLttIa0eI739svqZahoCZ8aHZY+gMhnl1Zx1pyX6W6Byt0gcVuvTpa89v482KBh6+eQ6TCzK9jjNsmBk3zSuitSPEb989RGZqgDnFOV7HkhimQpdzevzNffz0zf18+rIJ3FJW0uf20iUaqyUC+H3GbReV8Ngbe3l2QzV5GSmMzel9hUYR7bYoZ/Xqzjr+8bltvH96AfdfO8PrOMNWkr/rCNIRSX6eWLuflvag15EkRqnQpVdv7mngM4+/zYwxmXzvjvn4fdrLwkuZqUncuXg8LW1Bnl5XSVgrNEovVOjyHu9UHuGen65jXG4a//2pRWSkaGYuFhSPTOOGuWPZU3+cVeWHvY4jMUiFLqfZdrCJux97i7zMFJ64ZxG56cleR5IeysaP5IKxWbywtZaDR094HUdijApdTimva+GuH68lIyXAk/csYnRWqteR5AxmxkfmFZGe4ufpdVV0hsJeR5IYokIXAKoaW7nzR2sxM564ZxHFI9O8jiRnkZYS4OYFJdS3tPPydq35In+iydEEMtBd5ZpOdPLo6xWc6Ajx6csmsqaikTUVjVFOJ9E0uSCDsvEjeaO8njnF2dqVUQCN0Ie91vYgj63aS0t7kE9eUkphtqZZ4sW1s8aQnhzgl+9UEwprrxdRoQ9r7Z0hfvLmPhqPd3DX4vGU5GqaJZ6MSPZzw9yxHDzaxuo92utFVOjDVmcozH+v2c/Boye4Y+E4JuVneB1JBuCCsVlML8zk5R11NLV1eh1HPKZCH4ZCYcfP3qpk3+Hj3LygRGcdimNmxvWzxxAKO17YWuN1HPFYRIVuZkvNbKeZlZvZ/b3c/j4z22BmQTO7OfoxJZpWvHuIHTXN3DB3LPNKtNhTvBuVkcKlk/PYUHmUysZWr+OIh/osdDPzA48A1wIzgTvM7MwFsSuBTwJPRTugRNebFQ28WdHApZPzWDxxlNdxJEqumJZPVmqA5zYd1LIAw1gkI/SFQLlzrsI51wEsA27quYFzbp9zbjOgoxxiWHldC7/dfJDphZksnVXodRyJopSAn6WzCjlw9AQb9h/xOo54JJJCLwKqelyu7r6u38zsXjNbb2br6+vrB3IXMkBHWztYtq6SvIwUbisrwadTmiWcucU5jMtNY+XWGk50hLyOIx6IpNB7e+UP6D2dc+5R51yZc64sPz9/IHchAxAMhXnqrUpCYcedi8aTojMOJSQz44a5Y2ntCPHKjlqv44gHIin0aqDnmQ2KgYODE0cGw2/fPUT1kRPcvKCYvMwUr+PIICrKGUFZ6UjerGhgd22z13FkiEVS6OuAKWY2wcySgduB5YMbS6Jl+6Em1u5t5NLJeVwwNtvrODIErplZSHLAx0PPb8PpA9Jhpc9Cd84FgfuAlcB24Bnn3FYze8jMbgQws4vMrBq4BfiBmW0dzNASmea2Tp7dUM3Y7FQ+oLPGDxsZKQHeP300r+8+zEtavGtYiWhxLufcCmDFGdc92OPrdXRNxUiMCDvHL96upiMY5tayEgJ+HUM2nCyeOIqdtc18/bfbeN/UPFIC+txkONCrPEGtqWhgd10L180eQ4HWNR92/D7jwQ/NZH9DK4+9sc/rODJEVOgJqKapjd9vqWF6YSaLJuR6HUc88r6p+Vw9YzTff2U3dU1tXseRIaBCTzCdoTDPrKsiJcnPn11YjGl/82Htq9fPoDPk+Obvd3gdRYaACj3BvLC1hpqmNm6+sEgndxZK89L51KUT+OWGA7xTqSNIE50KPYHsrm1m1Z4GFk8cxbRCraAoXe67ajIFmSn843PbCOtEGAlNhZ4gGo938IsN1RRkpnCt1mmRHjJSAtx/7XQ2VR3l6fVVfX+DxC0VegJwzvHlZzfT2hHi1rISkrSLopzhI/OLWDwxl2+s2E5dsz4gTVR65SeAZeuqeHFbLR+YOVonC5ZemRn/9yOzaesM8/Xnt3sdRwaJCj3OVdS38NBz21gyeRRLJud5HUdi2KT8DP7qykks33SQ13bqCNJEpEKPY52hMF98eiMpST6+fcs8LYkrffrsFZOYXJDB/c++y7ETOgdpolGhx7GHV+5kc/UxvvGR2RRm62hQ6VtKwM93bp1LfUs7/7RcSy4lGhV6nHphaw2P/rGCuxaP59rZY7yOI3FkTnEOn7tyMr985wC/33LI6zgSRSr0OFTZ0MqXfr6J2UXZfPVDM7yOI3Hof101mVlFWTzwy3c5ePSE13EkSlToceZ4e5DPPPE2AP/+8Qu1ip4MSJLfx/dun09HMMznntpAR1CnA04EKvQ4Ego7vrBsIztqmvi3O+ZTkpvmdSSJY5PyM/jWzXN5p/Io/7xCuzImAhV6HPnm77bz0vZa/uGGC7hyWoHXcSQBXD9nDH++pJSfrN7Hs29Xex1HzpMKPU78+2vl/PD1vdx98XjuvqTU6ziSQB64dgaXTBrFl5/dzOu7672OI+dBhR4HfvCHPXzr9zu5ad5YHrzhAq/jSIJJDvj4z7sWMLkgg88+sYGtB495HUkGSIUew5xzfO+l3Xzjdzu4Ye5Yvn3LXPw+HTwk0ZeVmsR//flFZKYGuOvHb6nU45QKPUad6Ajx+WUb+e5Lu/iz+UV899a5Oi+oDKox2SN46tOLSQ34uOPRNWysOup1JOknNUQM2nLgGB/9j9U8v/kgX146nW+rzGWITMhL5+m/vJictGQ+/sM1vLC1xutI0g9qiRhyrLWTf16xnZseWUVdczs/vruMz14xSaeRkyFVkpvGM395MZMKMrj38bf5zou7dGKMOKFzlEXJU2srB/R9zjnqmtt5a18jm6qO0toR4o6F47h/6XSy05KinFKGk4H+Tp70zF9ezFd/vYV/e3k3b+1t4Jt/NofSvPQopYvM+f4MAB9bNC4KSeKDCn0IOOdwQHtnmNaOIMfaOqlvbufQsTZ21zZzpLUTn8GH5xVxz2UTmTlWp48T76Um+Xn45jksLM3la89v44P/+kc+//4pfGrJBEYk6wjlWKRCj9Dx9iC761rYU9dCTVMb9c3t1Da1UdfczpHjHRxp7SAYdgRDjpBzhMOOsHM4B2d7s5oc8DExL533Tc1nxpgsPnP5pCH9mUT6YmbcelEJl0/L5+9/vYWHV+7kJ6v38VdXTOLWshLSPT4Redg5jrV2UtfczrETnRw70cHxjhBtnSE6g2Ec8PL2WlKT/WQkBxiZnkzxyBHdf9IoHjmC1KTE+c9JhX6GzlCYvYePs6OmmV01zV1/1zZT2dh62naZqQFGZ6VSkJnCjLFZHDxygoDf8PuMgM+Hz7peDCf/NutaujQt2U9GSoCCzBSyRyRpflziwuisVB79RBnr9jXy7Rd28k/PbeP/rdzJjfOK+Mj8Ii4clzOoH9w75zh2oqu4a5vaqG1qp665jbqmdjpCf1qHxoARyX5Sk/ykBHwY4PcZJzpDHG8P0ni8g87Q6UOsMdmpTBmdydSCDKYWZjJ1dCZTCjI8/89qICJKbGZLge8BfuBHzrlvnnF7CvDfwAKgAbjNObcvulGj60RHiIrDLeypP86euhYqDh9nd20ze+pbTv2D+33GhLx0Zhdnc/OCYqYVdv1Dj8ke8Z63nNGY6xOJdReV5rLs3ot5e38jP3uril+9U83P3qoke0QSl03J48JxI5lbks2U0Zlkpfb/M6Dj7UH2N7Syr+E4ew8f55UddafeDbf3WEAsMyVAQVYKC0pHUpiZSkFWCjlpyWSkBN5zrEbPOfRQ2FHf3E71kVaqj5ygqrGVPfUt7KptYU1Fw2mLlBXljGDq6Iyugh+dydTRGUwuyCAtOXaLvs9kZnqMAlwAAAVDSURBVOYHHgGuAaqBdWa23Dm3rcdmfwEccc5NNrPbgX8BbhuMwOGwozMcJhhydIbCdIYcwXCYzmDX9R3BMC3tQZrbOmluC9LUFuTo8Q5quv9Xr21qOzVl8qefEYpHjmBKQSZXTi9g2uhMphVmMjE/XasZivRiwfhcFozP5R9umMkfdx3mlR11rCo/zPOb/7S++si0JIpGjiA3PYWcEUkEfHbq3aoBIec42tpJY/eU5ZHjHTS1BU97nIyUAHkZKcwryWF0VmrXn8wU0gY4evb7jMLsVAqzUykrPf22UNhR2djKrtpmdtc2s6u2hV21zawqbzj1LsAM8jNSKMzuylKY1XVf2SOSyEwNkJXa9XdGaoAkv49kv4+Av+td+6mv/UaSz4dvEA4SjORZWQiUO+cqun4gWwbcBPQs9JuAf+z++hfA983MnHNR39fpB3+s4F9+v6Pf35eTlkRh9y/EzDFZFI0cwaT8DCYVpFM6Kj2h5tFEhkpmahLXzxnD9XO6TrJS29TG5upjVNS3sL+xlYNHT3CktZP9DccJhbs/U+reScBnxsj0JEamJTMuN43c9GTyM1MoHZXO+FFplOals3zjwSH7WU6+I5+Ql84HLyg8dX0wFGZfQ+upkj9wtJWapnYqG1p5a2/jgE7l97UPz+KuxeOjGR8A66tzzexmYKlz7p7uy3cBi5xz9/XYZkv3NtXdl/d0b3P4jPu6F7i3++I0YGe0fpCzyAMO97nV8KHn43R6Pk6n5+N0sfp8jHfO5fd2QyQj9N7eF5z5v0Ak2+CcexR4NILHjAozW++cKxuqx4t1ej5Op+fjdHo+ThePz0ckH0tXAyU9LhcDZ74POrWNmQWAbKAxGgFFRCQykRT6OmCKmU0ws2TgdmD5GdssB+7u/vpm4JXBmD8XEZGz63PKxTkXNLP7gJV07bb4mHNuq5k9BKx3zi0Hfgw8bmbldI3Mbx/M0P0wZNM7cULPx+n0fJxOz8fp4u756PNDURERiQ9abVFEJEGo0EVEEsSwKXQz+1szc2aW53UWL5nZw2a2w8w2m9mvzCzH60xDzcyWmtlOMys3s/u9zuMlMysxs1fNbLuZbTWzL3idKRaYmd/M3jGz573O0h/DotDNrISupQu04Aq8CMxyzs0BdgEPeJxnSPVYyuJaYCZwh5nN9DaVp4LAl5xzM4DFwOeG+fNx0heA7V6H6K9hUejAd4H/w9lXsh02nHMvOOdOLpixhq7jCoaTU0tZOOc6gJNLWQxLzrlDzrkN3V8301ViRd6m8paZFQPXAz/yOkt/JXyhm9mNwAHn3Cavs8SgTwG/8zrEECsCqnpcrmaYF9hJZlYKzAfWepvEc/9K1wAw3NeGsSZ214HsBzN7CSjs5aavAH8HfGBoE3nrXM+Hc+433dt8ha63208OZbYYENEyFcONmWUAzwJfdM41eZ3HK2b2IaDOOfe2mV3hdZ7+SohCd85d3dv1ZjYbmABs6j6RRDGwwcwWOucS9nTmZ3s+TjKzu4EPAe8fhkf0RrKUxbBiZkl0lfmTzrlfep3HY0uAG83sOiAVyDKzJ5xzd3qcKyLD6sAiM9sHlJ25CuRw0n2yku8Alzvn6r3OM9S61xraBbwfOEDX0hYfc85t9TSYR6xrpPNToNE590Wv88SS7hH63zrnPuR1lkgl/By6vMf3gUzgRTPbaGb/6XWgodT9gfDJpSy2A88M1zLvtgS4C7iq+/dhY/foVOLQsBqhi4gkMo3QRUQShApdRCRBqNBFRBKECl1EJEGo0EVEEoQKXUQkQajQRUQSxP8AsK7jdaw3HtgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 数据准备\n",
    "\n",
    "a = np.random.randn(100)\n",
    "s = pd.Series(a)\n",
    "\n",
    "# 使用matplotlib画直方图\n",
    "plt.hist(s)\n",
    "plt.show()\n",
    "\n",
    "# 使用matplotlib画直方图\n",
    "sns.distplot(s, kde=False)\n",
    "plt.show()\n",
    "sns.distplot(s, kde=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 条形图\n",
    "\n",
    "如果说通过直方图可以看到变量的数值分布情况，我们通过条形图可以帮助我们看到类别的特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 数据准备\n",
    "x = ['Cat1', 'Cat2', 'Cat3', 'Cat4', 'Cat5']\n",
    "y = [5, 4, 8, 12, 7]\n",
    "\n",
    "# 用Matplotlib画条形图\n",
    "plt.bar(x, y)\n",
    "plt.show()\n",
    "\n",
    "# 用seaborn画条形图\n",
    "sns.barplot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 箱线图\n",
    "\n",
    "箱线图， 又称盒式图， 它与1977年提出的， 由五个数值点组成： \n",
    "- 最大值 （max)\n",
    "- 最小值 （min)\n",
    "- 中位数 (median)\n",
    "- 上下四分位数（Q3, Q1）\n",
    "\n",
    "它可以帮助我们分析出数据的差异性，离散程度和异常值等"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.09199559  0.58376911 -2.03678724 -0.99959162]\n",
      " [-2.05939221 -1.59419718  0.62258609 -0.45390457]\n",
      " [ 0.71449346  0.4864426  -3.03421597 -0.0929687 ]\n",
      " [ 1.4660722   2.01363199  0.32356902 -1.88108871]\n",
      " [ 0.80582839 -0.53708418 -1.85487548 -0.89515415]\n",
      " [ 1.05853763  0.2764954  -0.18533501 -2.73579903]\n",
      " [-0.6636136  -0.13488869 -2.43418492  0.08658482]\n",
      " [ 0.15540567 -0.80412236  0.37831814 -0.89271695]\n",
      " [-0.53283477 -0.46919518 -0.83326238  0.34848547]\n",
      " [ 1.11355552  0.63796271 -1.22980268 -0.58515534]]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "data = np.random.normal(size=(10,4))\n",
    "print(data)\n",
    "labels = ['A', 'B', 'C', 'D']\n",
    "\n",
    "# 用matplotlib画箱线图\n",
    "plt.boxplot(data, labels=labels)\n",
    "plt.show()\n",
    "\n",
    "# 用Seaborn画箱线图\n",
    "df = pd.DataFrame(data, columns = labels)\n",
    "sns.boxplot(data = df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 饼图\n",
    "\n",
    "饼图式常用的统计学模块，可以显示每个部分大小与总和之间的比例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 数据准备\n",
    "\n",
    "nums = [25, 37, 33, 37, 6]\n",
    "labels = ['HighSchool', 'Bacherlor', 'Master', 'Ph.d', 'Others']\n",
    "\n",
    "# 使用matplotlib画饼图\n",
    "\n",
    "plt.pie(x = nums, labels = labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 热力图\n",
    "\n",
    "英文叫 heat map, 是一种矩阵表示方法， 其中矩阵中的元素用颜色来代表，不同的颜色代表不同的大小。通过颜色就能直观的知道某个位置上的数值的大小。另外，你也可以将这个位置上的颜色，与数据集中的其他位置颜色进行比较\n",
    "\n",
    "热力图式一种非常直观的多元变量分析方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "# sphinx_gallery_thumbnail_number = 2\n",
    "\n",
    "vegetables = [\"cucumber\", \"tomato\", \"lettuce\", \"asparagus\",\n",
    "              \"potato\", \"wheat\", \"barley\"]\n",
    "farmers = [\"Farmer Joe\", \"Upland Bros.\", \"Smith Gardening\",\n",
    "           \"Agrifun\", \"Organiculture\", \"BioGoods Ltd.\", \"Cornylee Corp.\"]\n",
    "\n",
    "harvest = np.array([[0.8, 2.4, 2.5, 3.9, 0.0, 4.0, 0.0],\n",
    "                    [2.4, 0.0, 4.0, 1.0, 2.7, 0.0, 0.0],\n",
    "                    [1.1, 2.4, 0.8, 4.3, 1.9, 4.4, 0.0],\n",
    "                    [0.6, 0.0, 0.3, 0.0, 3.1, 0.0, 0.0],\n",
    "                    [0.7, 1.7, 0.6, 2.6, 2.2, 6.2, 0.0],\n",
    "                    [1.3, 1.2, 0.0, 0.0, 0.0, 3.2, 5.1],\n",
    "                    [0.1, 2.0, 0.0, 1.4, 0.0, 1.9, 6.3]])\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "im = ax.imshow(harvest)\n",
    "\n",
    "# We want to show all ticks...\n",
    "ax.set_xticks(np.arange(len(farmers)))\n",
    "ax.set_yticks(np.arange(len(vegetables)))\n",
    "# ... and label them with the respective list entries\n",
    "ax.set_xticklabels(farmers)\n",
    "ax.set_yticklabels(vegetables)\n",
    "\n",
    "# Rotate the tick labels and set their alignment.\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "         rotation_mode=\"anchor\")\n",
    "\n",
    "# Loop over data dimensions and create text annotations.\n",
    "for i in range(len(vegetables)):\n",
    "    for j in range(len(farmers)):\n",
    "        text = ax.text(j, i, harvest[i, j],\n",
    "                       ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "ax.set_title(\"Harvest of local farmers (in tons/year)\")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 蜘蛛图\n",
    "\n",
    "蜘蛛图是一种显示1对多关系的方法。在蜘蛛图中， 一个变量相对于另一个变量的显著性是清晰可见的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.font_manager import FontProperties\n",
    "# 数据准备\n",
    "labels=np.array([u\"推进\",\"KDA\",u\"生存\",u\"团战\",u\"发育\",u\"输出\"])\n",
    "stats=[83, 61, 95, 67, 76, 88]\n",
    "# 画图数据准备，角度、状态值\n",
    "\n",
    "angles=np.linspace(0, 2*np.pi, len(labels), endpoint=False)\n",
    "stats=np.concatenate((stats,[stats[0]]))\n",
    "angles=np.concatenate((angles,[angles[0]]))\n",
    "# 用Matplotlib画蜘蛛图\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, polar=True)\n",
    "ax.plot(angles, stats, 'o-', linewidth=2)\n",
    "ax.fill(angles, stats, alpha=0.25)\n",
    "# 设置中文字体\n",
    "font = FontProperties(fname=r\"C:\\Windows\\Fonts\\simhei.ttf\", size=14)\n",
    "ax.set_thetagrids(angles * 180/np.pi, labels, FontProperties=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
